Replace brittle “zap” automation with AI agents that understand your workflows
We help you move beyond hundreds of Zapier / Make / n8n flows and into AI agents that orchestrate your APIs using Model Context Protocol (MCP). Fewer boxes and arrows; more business outcomes.
From “zap sprawl” to unified agents
Replace long chains of zaps/scenarios with a small number of robust agents that plan and execute workflows end-to-end.
API-first, not UI-scraping
Agents call your APIs via MCP tools. No fragile DOM selectors, no surprise UI changes breaking flows.
Built for scale, not hobby projects
Observability, limits, and governance for automations that touch revenue, customers, and operations.
Your Zapier-style layer started as a shortcut. Now it's a second product to maintain.
Zapier, Make, and n8n are great for quick wins. But once you cross a certain threshold, you get a shadow integration layer that's hard to govern and harder to reason about.
Symptoms of automation sprawl
- Hundreds of flows named “Copy of…”, “New 3 (final)” and no clear owner.
- Critical business logic living in a vendor UI instead of your codebase.
- Flows silently failing on rate limits, schema changes, or auth errors.
- “Who owns this automation?” becomes a recurring incident question.
What an AI agent layer changes
- Agents that understand intent, not just triggers: “When a customer churns, do the right sequence.”
- Logic lives in versioned MCP tools and prompts, not in a proprietary GUI.
- AI can adapt to minor changes (like new fields) without manual re-wiring.
- One agent can coordinate across many systems instead of chaining dozens of flows.
Replace brittle glue with agents that orchestrate via MCP
We design and implement AI agents that call your systems through MCP tools—so workflows live in one coherent agent brain instead of a spaghetti of triggers and filters.
Map current automations
We audit your Zapier / Make / n8n flows and identify the 10–20 core workflows that actually matter.
Design MCP tools
We turn those workflows into MCP tools and APIs with clear schemas and guardrails—no brittle UI scraping.
Implement AI agents
We create agents that understand user intent, choose the right tools, and orchestrate multi-step flows.
Cut over & decommission glue
We migrate traffic, monitor behavior, and gradually turn off legacy flows to reduce surface area and failure modes.
Instead of each workflow being a separate zap or scenario, agents call a shared set of MCP tools that wrap your APIs—centralizing logic and reducing duplication.
Zapier-style glue vs AI agents on MCP
A simple way to see it: boxes-and-arrows tied to one vendor vs. agentic workflows built on your own APIs and infrastructure.
Zapier / Make / n8n layer
- • Logic distributed across many flows and vendors.
- • Limited reasoning: complex branching becomes a mess.
- • UI or connector changes can break critical automations.
- • Hard to version, test, and review like normal code.
- • Mostly trigger/response: no planning of multi-step tasks.
AI agents on MCP
- • Central agent layer that plans and executes workflows.
- • Tools wrap your APIs with clear schemas and constraints.
- • Reasoning + planning: agents can recover, retry, and adapt.
- • Logic versioned in code, prompts, and MCP tool configs.
- • Reusable toolset: one set of tools used by many agents and flows.
High-value workflows to move from glue to agents
We start with the automations that are high-impact and high-maintenance—where replacing glue with agents actually pays off.
Lead routing & enrichment
Instead of five zaps to enrich a lead, update CRM, and notify sales, an agent orchestrates the workflow based on lead context and your playbooks.
Customer lifecycle flows
Agents that handle trial-to-paid, churn risk, expansion opportunities, and renewal sequences across billing, CRM, and messaging systems.
Ops & back-office automation
From “create purchase order, route for approval, update ERP, and notify finance” to a single agent-managed workflow instead of a multi-zap chain.
When a user starts a trial from DACH, enroll them in our high-touch onboarding sequence.
Agent plan
1) Check trial metadata in billing system
2) Create CRM task for CSM
3) Add user to onboarding email sequence
4) Create Slack notification for sales channel
Tools used: trial_query, crm_create_task, email_enroll_sequence, slack_post_message
Done. I've enrolled the user in the DACH onboarding flow, notified the sales channel, and created a CSM task with full context.
Who this is for
We're a good fit if Zapier / Make / n8n is no longer a “nice tool” but a critical layer you feel nervous about.
B2B SaaS with many cross-tool automations
RevOps & BizOps teams drowning in zaps
Ops-heavy businesses with many SaaS integrations
Engineering teams wanting API-first automation
Companies aiming for AI-native operations
Leaders tired of surprise automation breakages
What we optimize for
We measure against time saved, risk reduced, and how many flows you can safely retire.
Time-to-change
How quickly can you change a workflow when business rules change—without touching 12 separate zaps?
Operational risk
Fewer silent failures, clearer ownership, and better observability for business-critical flows.
Outcome throughput
More workflows successfully completed per week, not more zaps created per week.
Strategic migration, not another integration project
We're replacing infrastructure you rely on daily. This is deliberate, high-skill work priced as a premium B2B engagement.
Automation → Agents Migration
Replace Zapier-style, Make, n8n glue with AI agents
Investment: premium, by proposal
Scoped around number of flows, systems involved, and how deep the agents go into your operations.
A typical engagement includes
- • Automation inventory & risk assessment
- • MCP tool & agent architecture design
- • Implementation of core agents & tools
- • Cut-over plan & decommissioning support
Optional add-ons
- • Ongoing AI ops & monitoring
- • Additional agents for new workflows
- • Internal enablement & documentation
- • Integration with ChatGPT / Claude / internal UIs
If you're managing dozens or hundreds of automations across Zapier, Make, or n8n—and want to grow without multiplying that complexity—this is the right time to explore an agent-first approach.
Request an automation auditReady to retire your zap jungle?
Show us your current automation layer—Zapier, Make, n8n, or a mix—and tell us which workflows you'd never want to break. We'll design an MCP + AI agent architecture to take you from brittle glue to durable, AI-native operations.